Microservices Architecture and Design patterns
- What are microservices?
In short, the microservice architectural style is an approach to developing a single application as a suite of small services,
each running in its own process and communicating with lightweight mechanisms, often an HTTP resource API. These
services are built around business capabilities and independently deployable by fully automated deployment machinery.
There is a bare minimum of centralized management of these services, which may be written in different programming languages
and use different data storage technologies.
each running in its own process and communicating with lightweight mechanisms, often an HTTP resource API. These
services are built around business capabilities and independently deployable by fully automated deployment machinery.
There is a bare minimum of centralized management of these services, which may be written in different programming languages
and use different data storage technologies.
-- James Lewis and Martin Fowler
- Scoping microservices
- Domain-driven-design
- Ubiquitous language
- Bounded context
- API-based microservices
- API architectural styles
- REST (Pragmatic REST)
- HATEOS (True REST)
- SOAP
- RPC
- API architectural patterns
- Façade Pattern
- Proxy Pattern
- Stateless service pattern
- Async microservices
- Why async microservices?
- Fire and Forget Interactions
- Long running jobs
- Decoupled client and services
- Better user experience
- Event based
- Competing Worker Pattern
Subscribers compete for message (Eg. Rabbit MQ Direct Exchange)
- Fanout Pattern
Multiple consumers get the message (Eg. Rabbit MQ Fanout Exchange)
- Async API calls
- Microservices Composition Pattern
Used to compose microservices together.
- Broker
- Aggregate
- Chained
- Proxy
- Branch
- Data consistency across the microservices
- Two-phase commit
- Saga pattern
- Eventual Consistency
- Split monolithic databases across microservices
- Data First vs. Function first
- Patterns for DB design
- Event driven (Event-Carried State Transfer)
This pattern shows up when you want to update clients of a system in such a way that they don't need to contact
the source system in order to do further work. A source system might fire off events whenever a customer changes
their details with events that contain details of the data that changed. A recipient can then update its own copy of
customer data with the changes, so that it never needs to talk to the main customer system in order to do its work in the future.
the source system in order to do further work. A source system might fire off events whenever a customer changes
their details with events that contain details of the data that changed. A recipient can then update its own copy of
customer data with the changes, so that it never needs to talk to the main customer system in order to do its work in the future.
- Event sourcing
The core idea of event sourcing is that whenever we make a change to the state of a system, we record that state change as
an event, and we can confidently rebuild the system state by reprocessing the events at any time in the future. The event store
becomes the principal source of truth, and the system state is purely derived from it. The best example of this is a version-control
system. The log of all the commits is the event store and the working copy of the source tree is the system state.
an event, and we can confidently rebuild the system state by reprocessing the events at any time in the future. The event store
becomes the principal source of truth, and the system state is purely derived from it. The best example of this is a version-control
system. The log of all the commits is the event store and the working copy of the source tree is the system state.
- CQRS
- Greenfield database approach
- Brownfield migration approach
- Make microservices more resilient
- Patterns and approaches
- Timeout
Minimises’ the risk for exhausting all the threads in a thread pool and stops from system to go down.
- Circuit breaker
- Retry
- Bulkhead
Ex. Separating resources
Ex. Isolating microservices
Ex. Redundancy using load balancers and message brokers
- Microservices backward compatibility
Request Header versioning:
Request path versioning:
- Centralized Logging
Centralized logging considerations:
How to achieve consistent logging format?
Logging levels: 
Transaction transparency: 
- Microservices configurations
- Deployment servers
- Eternalized configurations
- Configuration management tools
Chef Overview:
Puppet Overview: 
- Containers
- Microservices registration and discovery
- Client side discovery
Example:
- Server side discovery
- Service registration
Self-registration:
Third-party registration:
- Tools
- Monitoring Microservices
- Monitoring key metrics
- Monitoring SLA metrics
- Dashboards
- Alerting and monitoring
- Defining thresholds for alerts
- Microservices monitoring pattern
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